PFΔScreen - an open-source tool for automated PFAS feature prioritization in non-target HRMS data.

Per- and polyfluoroalkyl substances (PFAS) are a huge group of anthropogenic chemicals with unique properties that are used in countless products and applications. Due to the high stability of their C-F bonds, PFAS or their transformation products (TPs) are persistent in the environment, leading to ubiquitous detection in various samples worldwide. Since PFAS are industrial chemicals, the availability of authentic PFAS reference standards is limited, making non-target screening (NTS) approaches based on high-resolution mass spectrometry (HRMS) necessary for a more comprehensive characterization. NTS usually is a time-consuming process, since only a small fraction of the detected chemicals can be identified. Therefore, efficient prioritization of relevant HRMS signals is one of the most crucial steps. We developed PFΔScreen, a Python-based open-source tool with a simple graphical user interface (GUI) to perform efficient feature prioritization using several PFAS-specific techniques such as the highly promising MD/C-m/C approach, Kendrick mass defect analysis, diagnostic fragments (MS2), fragment mass differences (MS2), and suspect screening. Feature detection from vendor-independent MS raw data (mzML, data-dependent acquisition) is performed via pyOpenMS (or custom feature lists) with subsequent calculations for prioritization and identification of PFAS in both HPLC- and GC-HRMS data. The PFΔScreen workflow is presented on four PFAS-contaminated agricultural soil samples from south-western Germany. Over 15 classes of PFAS (more than 80 single compounds with several isomers) could be identified, including four novel classes, potentially TPs of the precursors fluorotelomer mercapto alkyl phosphates (FTMAPs). PFΔScreen can be used within the Python environment and is easily automatically installable and executable on Windows. Its source code is freely available on GitHub ( https://github.com/JonZwe/PFAScreen ).

Non-extractable PFAS in functional textiles - characterization by complementary methods: oxidation, hydrolysis, and fluorine sum parameters.

Per- and polyfluoroalkyl substances (PFAS) are widely used for durable water-repellent finishing of different fabrics and textiles such as outdoor clothing, carpets, medical textiles and more. Existing PFAS extraction techniques followed by target analysis are often insufficient for detecting widely used side-chain fluorinated polymers (SFPs) that are barely or non-extractable. SFPs are typically copolymers consisting of a non-fluorinated backbone with perfluoroalkyl side-chains to obtain desired properties. We compared the accessible analytical information and performance of complementary techniques based on oxidation (dTOP and PhotoTOP assays), hydrolysis (THP assay), standard extraction, extractable organic fluorine (EOF), and total fluorine (TF) with five functional textiles and characterized 7 further textiles only by PhotoTOP oxidation. The results show that when applied directly to textile samples, dTOP and PhotoTOP oxidation and also hydrolysis (THP) are able to capture large fractions of TF in the form of perfluoroalkyl side-chains present in the textiles while methods relying on extracts (EOF, target and non-target analysis) yield much lower fractions of TF (e.g., factor ∼25-50 lower). The conversion of large fractions of the measured TF into PFCAs or FTOHs from fluorinated side chains is in contrast to previous studies. Concentrations ranged from

Photocatalytical transformation of fluorotelomer- and perfluorosulfonamide-based PFAS on mineral surfaces and soils in aqueous suspensions.

Per- and polyfluorinated substances (PFAS) are widely used industrial and household chemicals and occur on various contaminated field sites. To better understand their behavior on soils, spike experiments were performed with 6:2 diPAP (6:2 polyfluoroalkyl phosphate diester) on pure mineral phases (titanium dioxide, goethite and silicon dioxide) in aqueous suspensions under artificial sunlight. Further experiments were performed with uncontaminated soil and four precursor PFAS. Titanium dioxide (referenced as 100 %) showed the highest reactiveness to transform 6:2 diPAP to its primary metabolite 6:2 fluorotelomer carboxylic acid, followed by goethite with the addition of oxalate (4.7 %), silicon dioxide (1.7 %) and soil (0.0024 %). Experiments with four precursors [6:2 diPAP, 6:2 fluorotelomer mercapto alkyl phosphate (FTMAP), N-ethyl perfluorooctane sulfonamide ethanol-based phosphate diester (diSAmPAP), N-ethyl perfluorooctane sulfonamidoacetic acid (EtFOSAA)] on natural soils showed a transformation of all four precursors by simulated sunlight. The production of the primary intermediate from 6:2 FTMAP (6:2 FTSA, rate constant k = 2.7∗10-3h-1) was approximately 13-times faster than from 6:2 diPAP (6:2 FTCA, rate constant k = 1.9∗10-4h-1). EtFOSAA was completely decomposed within 48 h whereas only ~7 % diSAmPAP was transformed in the same time. The primary photochemical transformation product of diSAmPAP and EtFOSAA was PFOA, PFOS was not detected. The production rate constant of PFOA varied significantly between EtFOSAA (k = 0.01h-1) and diSAmPAP (k = 1.3∗10-3h-1). Photochemically produced PFOA consisted of branched and linear isomers and can therefore be used in source tracking. Experiments with different soils suggest that the oxidation of EtFOSAA to PFOA is expected to primarily be driven by hydroxyl radicals, whereas for the oxidation of EtFOSAA to further intermediates, another mechanism instead or in addition to the oxidation by hydroxyl radicals is responsible.

PFAS-Contaminated Soil Site in Germany: Nontarget Screening before and after Direct TOP Assay by Kendrick Mass Defect and FindPFΔS.

Soil contaminations with per- and polyfluoroalkyl substances (PFAS) are of great concern due to their persistence, leading to continuous, long-term groundwater contamination. A composite sample from contaminated agricultural soil from northwestern Germany (Brilon-Scharfenberg, North Rhine-Westphalia) was investigated in depth with nontarget screening (NTS) (Kendrick mass defect and MS2 fragment mass differences with FindPFΔS). Several years ago, selected PFCAs and PFSAs were identified on this site by detection in nearby surface and drinking water. We identified 10 further PFAS classes and 7 C8-based PFAS (73 single PFAS) previously unknown in this soil including some novel PFAS. All PFAS classes except for one class comprised sulfonic acid groups and were semi-quantified with PFSA standards from which ∼97% were perfluorinated and are not expected to be degradable. New identifications made up >75% of the prior known PFAS concentration, which was estimated to >30 µg/g. Pentafluorosulfanyl (-SF5) PFSAs are the dominant class (∼40%). Finally, the soil was oxidized with the direct TOP (dTOP) assay, revealing PFAA precursors that were covered to a large extent by identified H-containing PFAS and additional TPs (perfluoroalkyl diacids) were detected after dTOP. In this soil, however, dTOP + target analysis covers <23% of the occurring PFAS, highlighting the importance of NTS to characterize PFAS contaminations more comprehensively.

Efficient PFAS prioritization in non-target HRMS data: systematic evaluation of the novel MD/C-m/C approach.

Non-target screening (NTS) based on high-resolution mass spectrometry (HRMS) is necessary to comprehensively characterize per- and polyfluoroalkyl substances (PFAS) in environmental, biological, and technical samples due to the very limited availability of authentic PFAS reference standards. Since in trace analysis, MS/MS information is not always achievable and only selected PFAS are present in homologous series, further techniques to prioritize measured HRMS data (features) according to their likelihood of being PFAS are highly desired due to the importance of efficient data reduction during NTS. Kaufmann et al. (J AOAC Int, 2022) presented a very promising approach to separate selected PFAS from sample matrix features by plotting the mass defect (MD) normalized to the number of carbons (MD/C) vs. mass normalized to the number of C (m/C). We systematically evaluated the advantages and limitations of this approach by using ~ 490,000 chemical formulas of organic chemicals (~ 210,000 PFAS, ~ 160,000 organic contaminants, and 125,000 natural organic matter compounds) and calculating how efficiently, and especially which, PFAS can be prioritized. While PFAS with high fluorine content (approximately: F/C > 0.8, H/F < 0.8, mass percent of fluorine > 55%) can be separated well, partially fluorinated PFAS with a high hydrogen content are more difficult to prioritize, which we discuss for selected PFAS. In the MD/C-m/C approach, even compounds with highly positive MDs above 0.5 Da and hence incorrectly assigned to negative MDs can still be separated from true negative mass defect features by the normalized mass (m/C). Furthermore, based on the position in the MD/C-m/C plot, we propose the estimation of the fluorine fraction in molecules for selected PFAS classes. The promising MD/C-m/C approach can be widely used in PFAS research and routine analysis. The concept is also applicable to other compound classes like iodinated compounds.

PhotoTOP: PFAS Precursor Characterization by UV/TiO2 Photocatalysis.

To unravel the complexity of per- and polyfluoroalkyl substances (PFAS) in products and environmental samples, sum parameters that provide relevant information on chemical characteristics are necessary since not all PFAS can be captured by target analysis in case of missing reference standards or if they are not extractable or amenable to the analytical method. Therefore, we evaluated photocatalysis (UV/TiO2) as a further total oxidizable precursor approach (PhotoTOP) to characterize perfluoroalkyl acid precursors via their conversion to perfluoroalkyl carboxylic acids (PFCAs). Photocatalysis has the advantage that no salts are needed, allowing direct injection with liquid chromatography-mass spectrometry without time-consuming and potentially discriminating sample cleanup. OH radicals were monitored with OH probes to determine the reactivity. For eight different precursors (diPAPs, FTSAs, FTCAs, N-EtFOSAA, PFOSA), mass balance was achieved within 4 h of oxidation, and also, in the presence of matrix, complete conversion was possible. The PhotoTOP was able to predict the precursor chain length of known and here newly identified precursors qualitatively when applied to two PFAS-coated paper samples and technical PFAS mixtures. The length of the perfluorinated carbon chain (n) was mostly conserved in the form of PFCAs (n-1) with only minor fractions of shorter-chain PFCAs. Finally, an unknown fabric sample and a polymer mixture (no PFAS detectable in extracts) were oxidized, and the generated PFCAs indicated the occurrence of side-chain fluorinated polymers.

FindPFΔS: Non-Target Screening for PFAS─Comprehensive Data Mining for MS2 Fragment Mass Differences.

The limited availability of analytical reference standards makes non-target screening approaches based on high-resolution mass spectrometry increasingly important for the efficient identification of unknown PFAS (per- and polyfluoroalkyl substances) and their TPs. We developed and optimized a vendor-independent open-source Python-based algorithm (FindPFΔS = FindPolyFluoroDeltas) to search for distinct fragment mass differences in MS/MS raw data (.ms2-files). Optimization with PFAS standards, two pre-characterized paper and soil samples (iterative data-dependent acquisition), revealed Δ(CF2)n, ΔHF, ΔCnH3F2n-3, ΔCnH2F2n-4, ΔCnHF2n-5, ΔCnF2nSO3, ΔCF3, and ΔCF2O as relevant and selective fragment differences depending on applied collision energies. In a PFAS standard mix, 94% (36 of 38 compounds from 10 compound classes) could be found by FindPFΔS. The use of fragment differences was applicable to a wide range of PFAS classes and appears as a promising new approach for PFAS identification. The influence of mass tolerance and intensity threshold on the identification efficiency and on the detection of false positives was systematically evaluated with the use of selected HR-MS2-spectra (20,998) from MassBank. To this end, with the use of FindPFΔS, we could identify different unknown PFAS homologues in the paper extracts. FindPFΔS is freely available as both Python source code on GitHub (https://github.com/JonZwe/FindPFAS) and as an executable windows application (https://doi.org/10.5281/zenodo.6797353) with a graphical user interface on Zenodo.

Electrochemical Oxidation of 6:2 Polyfluoroalkyl Phosphate Diester-Simulation of Transformation Pathways and Reaction Kinetics with Hydroxyl Radicals.

Polyfluoroalkyl phosphate diesters (diPAPs) are widely used for paper and cardboard impregnation and discharged via waste streams from production processes and consumer products. To improve the knowledge about the environmental fate of diPAPs, electrochemical oxidation (EO) was used to characterize the transformation pathways and reaction kinetics. 6:2 diPAP was transformed electrochemically to perfluorocarboxylic acids (C5-C7 PFCAs) and two intermediates (6:2 fluorotelomer carboxylic acid, FTCA, and 6:2 fluorotelomer unsaturated carboxylic acid, FTUCA). EO of potential intermediates 6:2 monoPAP and 6:2 fluorotelomer alcohol (FTOH) showed similar transformation products but with different ratios. We show that 6:2 diPAP is initiated by OH radical (•OH) reactions, as evidenced by the measured steady-state concentrations of •OH with the probe molecule terephthalic acid, quenching experiments, and pH dependency of the reaction. PFHpA was the main product of 6:2 diPAP oxidation, and it was formed in a pseudo-first-order reaction for which a bimolecular rate constant was estimated to be kO•H,diPAPformPFHpA = 9.4(±1.4) × 107 M-1 s-1 by an initial rate approach. This can be utilized to estimate the environmental half-life of 6:2 diPAP for the reaction with •OH and the formation kinetics of persistent PFCAs.